Can rates of ocean primary production and biological carbon export be related through their probability distributions?

Cael, B. B. ORCID: https://orcid.org/0000-0003-1317-5718; Bisson, Kelsey; Follett, Christopher L.. 2018 Can rates of ocean primary production and biological carbon export be related through their probability distributions? Global Biogeochemical Cycles, 32 (6). 954-970. https://doi.org/10.1029/2017GB005797

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Abstract/Summary

We describe the basis of a theory for interpreting measurements of two key biogeochemical fluxes—primary production by phytoplankton (p, μg C · L−1 · day−1) and biological carbon export from the surface ocean by sinking particles (f, mg C · m−2 · day−1)—in terms of their probability distributions. Given that p and f are mechanistically linked but variable and effectively measured on different scales, we hypothesize that a quantitative relationship emerges between collections of the two measurements. Motivated by the many subprocesses driving production and export, we take as a null model that large‐scale distributions of p and f are lognormal. We then show that compilations of p and f measurements are consistent with this hypothesis. The compilation of p measurements is extensive enough to subregion by biome, basin, depth, or season; these subsets are also well described by lognormals, whose log‐moments sort predictably. Informed by the lognormality of both p and f we infer a statistical scaling relationship between the two quantities and derive a linear relationship between the log‐moments of their distributions. We find agreement between two independent estimates of the slope and intercept of this line and show that the distribution of f measurements is consistent with predictions made from the moments of the p distribution. These results illustrate the utility of a distributional approach to biogeochemical fluxes. We close by describing potential uses and challenges for the further development of such an approach.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2017GB005797
ISSN:	0886-6236
Date made live:	25 Apr 2020 13:44 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/527321

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